Artificial intelligence in payroll done right: building an AI assistant your team can trust

Generative AI can be a powerful business knowledge service, saving considerable time for employees. Yet concerns grow around AI accuracy and how it handles sensitive information. According to a 2025 KPMG survey, only 46% of company workers trust AI, and that proportion is shrinking, especially since 56% report making more mistakes because of AI.

Despite growing doubts, the technology can be an exceptional information source and time-saver, especially for sensitive, technical, and contextual queries. The challenge lies in building AI systems that are accurate, secure, and worthy of trust.

The payroll opportunity for AI

Payroll staff spend considerable time answering routine questions: Why did someone's net pay decrease? What amount of taxes were paid? How much overtime did an employee earn last month? Beyond simple queries, payroll teams also handle complex questions around formulas and components, regulations, payroll statuses across different business units, and structuring new payroll systems.

For payroll professionals, generative AI could streamline these daily tasks and free staff to focus on strategic work. But can AI handle these queries whilst adding real context, maintaining accuracy, and protecting sensitive data? The answer requires trust, accuracy, and rigorous oversight.

Building an AI assistant worthy of payroll

Generative AI excels at conversing in natural language, changing how we interact with technology. Search engines already produce AI-compiled answers users can expand with follow-up questions. Yet search answers are relatively simple, payroll AI must meet much higher standards.

Payroll information is highly contextual, and any AI system must reflect that reality. Payroll environments are also filled with private information, security requirements, and regulations that demand strict oversight and access controls. These stipulations define the baseline for useful generative AI in payroll.

AI Assist is a payroll assistant designed to answer contextualised payroll questions tailored to the person asking. Employees receive specific answers about their payslips, from tax paid to deductions and overtime. Payroll staff use AI Assist to explore payroll components and formulas, handle detailed queries, and access the PaySpace platform's knowledge base, receiving answers relevant to their organisation's specific payroll setup.

How to build trust in payroll AI

Being helpful is not enough. Generative AI can make mistakes, and organisations have legitimate concerns: Can someone use AI to access other employees' salaries? Will it unearth forgotten or unsupervised data? What about data leaks? What if sensitive information becomes embedded in the AI model itself?

These concerns are valid and crucial to address.

A conservative approach to AI security

AI Assist's features follow a conservative approach, with several important safeguards established from the outset:

• The AI is native to the PaySpace platform, not an external integration, ensuring unified security and control.
• It conforms to ISO and SOC compliance standards, meeting rigorous information security requirements.
• Users see only data they have authority to access—for example, staff members cannot ask AI Assist about other employees' salaries unless they have explicit permission to view that information.
• If a feature cannot meet these criteria, it is shelved until it can.

How sensitive data stays protected

Every interaction with AI Assist creates a temporary instance on secure Microsoft Azure cloud infrastructure. No customer data leaves that secure environment, and data access is strictly controlled by the user's profile as determined by the PaySpace platform. Critically, customer data cannot be used to train the AI model—reducing the risk of data leaks and ensuring the model doesn't 'memorise' sensitive information.

Reducing hallucinations and improving accuracy

To reduce the risk of hallucinations and other mistakes, the system doesn't rely solely on the AI model. Instead, it runs subsystems that handle specific queries and data access, passing verified information to the AI. This hybrid architecture has two critical advantages:

• It prevents data from leaking into the AI model during training.
• It improves answer accuracy because the mechanisms linking data with AI Assist are directly controlled and verified.

Making AI intuitive and effective for payroll

Hype and misconceptions cloud generative AI's potential. Deel Local Payroll sidesteps these issues by focusing on the technology's most obvious value and deliberately slowing development to ensure maximum, focused benefits.

The approach starts from a simple premise: How can generative AI make things easier for customers, whether they are working on payroll or need answers from payroll? The focus is on creating thoughtful communication that delivers answers people can trust. This remains difficult because generative AI is new technology with many unknowns. As a result, development moves carefully, testing is approached thoughtfully, and customers are involved through user engagements and beta testing.

Artificial intelligence: changing payroll for the better

The results are already remarkable, and generative AI is expected to change payroll and every aspect of how businesses engage with business information. Generative AI, when done right, with security, accuracy, and trust at the centre, is changing business for the better.

The key is rejecting hype and focusing relentlessly on solving real problems for real people.